Did It Really Work? What U.S. Policy Data Tells Us About Medicaid, Wages, and Causal Impact

In 2015, Seattle became the first major U.S. city to raise its minimum wage to $15. Headlines warned of mass job loss. But what really happened? Let’s dive into the data and see what public evidence reveals.

1. Why Causality Matters More Than Ever

In a world overflowing with dashboards, it’s easy to spot what changed. But it’s harder — and far more important — to answer: why did it change?
Was it the new policy? A cultural shift? Or just noise in the numbers?

In the age of correlation, we crave causality. Not just to track trends, but to understand impact — and responsibility.

That’s where causal inference comes in. It’s not just a method. It’s how data becomes truth.

And in this article, we’ll show how anyone — with Python and real public data — can detect causal effects from real-world U.S. policies.

2. A Quick Primer on Causal Thinking

Here’s a simple cheat sheet for the four core methods analysts use: